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Social and Behavioral Sciences Commons™
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- Automated guided vehicle systems (3)
- Machine learning (3)
- Traffic engineering (3)
- Feedback control systems (2)
- H [infinity symbol] control (2)
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- Intelligent control systems (2)
- Traffic accident investigation (2)
- Traffic accidents (2)
- Traffic flow (2)
- Travel time (Traffic engineering) (2)
- Artificial intelligence (1)
- Automated highway system (AHS) (1)
- Automatic control (1)
- Channel estimation (1)
- Compressed sensing (1)
- Doppler shift (1)
- Elevation and azimuth angles (1)
- Express highways (1)
- Intelligent vehicle control (1)
- Java (Computer program language) (1)
- Kalman filtering (1)
- Orthogonal frequency division multiplexing (1)
- Probabilistic automata (1)
- Ramp metering (Traffic engineering) (1)
- Ramp-freeway junctions (1)
- Reinforcement learning (1)
- Robust control (1)
- Stochastic learning automata (1)
- Time (1)
- Traffic congestion (1)
Articles 1 - 10 of 10
Full-Text Articles in Social and Behavioral Sciences
Elevation And Azimuth-Aided Channel Estimation Scheme For Airborne Hyperspectral Data Transmission, Vahid Vahidi, Ebrahim Saberinia
Elevation And Azimuth-Aided Channel Estimation Scheme For Airborne Hyperspectral Data Transmission, Vahid Vahidi, Ebrahim Saberinia
Electrical & Computer Engineering Faculty Research
A channel-estimation (CE) scheme is proposed to estimate the complex amplitude, Doppler shift, angle-of-departure, and angle-of-arrival of the channel taps for sparse and doubly selective channels for hyperspectral image transmission from unmanned aircraft vehicles (UAVs) to ground stations. The proposed method is dubbed as compressed-sensing joint parameter estimation (CS-JPE) and finds the channel parameters matrix by employing a compressed-sensing (CS)-based method. Afterward, a modified version of the joint parameter estimation (JPE) is proposed as CS-JPE and is dubbed as M-CS-JPE, which employs the elevation-azimuth angles of the line-of-sight channel tap to estimate the channel parameters with higher accuracy and lower …
Real-Time Travel Time Estimation Using Macroscopic Traffic Flow Models, Pushkin Kachroo, Kaan Ozbay, Antoine G. Hobeika
Real-Time Travel Time Estimation Using Macroscopic Traffic Flow Models, Pushkin Kachroo, Kaan Ozbay, Antoine G. Hobeika
Electrical & Computer Engineering Faculty Research
This paper presents the estimation of travel time on highways based on macroscopic modelling. The focus is on real-time values as compared to average or static values. The macroscopic models are used for distributed and time/space lumped settings and corresponding travel time estimation functions and algorithms are developed. The implications of these algorithms for the implementation of various incident management and traffic control strategies are also discussed.
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Isolated Ramp Metering Feedback Control Utilizing Mixed Sensitivity For Desired Mainline Density And The Ramp Queues, Pushkin Kachroo, Kaan Ozbay, Donald E. Grove
Electrical & Computer Engineering Faculty Research
This paper presents a feedback control design for isolated ramp metering control. This feedback control design, unlike the existing isolated feedback ramp controllers, also takes into account the ramp queue length. Using a nonlinear H∞ control design methodology, we formulate the problem in the desired setting to be able to utilize the results of the methodology.
Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay
Multiple Stochastic Learning Automata For Vehicle Path Control In An Automated Highway System, Cem Unsal, Pushkin Kachroo, John S. Bay
Electrical & Computer Engineering Faculty Research
This paper suggests an intelligent controller for an automated vehicle planning its own trajectory based on sensor and communication data. The intelligent controller is designed using the learning stochastic automata theory. Using the data received from on-board sensors, two automata (one for lateral actions, one for longitudinal actions) can learn the best possible action to avoid collisions. The system has the advantage of being able to work in unmodeled stochastic environments, unlike adaptive control methods or expert systems. Simulations for simultaneous lateral and longitudinal control of a vehicle provide encouraging results
Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay
Validation Of Waimss Incident Duration Estimation Model, Wei Wu, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
This paper presents an effort to validate the traffic incident duration estimation model of WAIMSS (wide area incident management support system). Duration estimation model of WAIMSS predicts the incident duration based on an estimation tree which was calibrated using incident data collected in Northern Virginia. Due to the limited sample size, a full scale test of the distribution, mean and variance of incident duration was performed only for the root node of the estimation tree, white only mean tests were executed at all other nodes whenever a data subset was available. Further studies were also conducted on the model error …
Wide-Area Incident Management System On The Internet, Kaan Ozbay, Pushkin Kachroo
Wide-Area Incident Management System On The Internet, Kaan Ozbay, Pushkin Kachroo
Electrical & Computer Engineering Faculty Research
The incident management process consists of four sequential steps-incident detection, response, clearance and recovery. Each of these components comprises of a number of operations and coordinated decision-making between the agencies involved. The provision of computer based support tools for the personnel involved will help develop appropriate strategies and increase efficiency and expediency. Existing systems are developed on various traditional computing platforms. However, with the advent of World Wide Web and Internet based programming tools such as Java, it is now possible to develop platform independent decision support tools for the incident management agencies. Any agency will be able to use …
Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay
Simulation Study Of Learning Automata Games In Automated Highway Systems, Cem Unsal, Pushkin Kachroo, John S. Bay
Electrical & Computer Engineering Faculty Research
One of the most important issues in Automated Highway System (AHS) deployment is intelligent vehicle control. While the technology to safely maneuver vehicles exists, the problem of making intelligent decisions to improve a single vehicle’s travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of …
Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan
Investigating The Use Of Kalman Filtering Approaches For Dynamic Origin-Destination Trip Table Estimation, Pushkin Kachroo, Kaan Ozbay, Arvind Narayanan
Electrical & Computer Engineering Faculty Research
This paper studies the applicability of Kalman filtering approaches for network wide traveler origin-destination estimation from link traffic volumes. The paper evaluates the modeling assumptions of the Kalman filters and examines the implications of such assumptions.
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Feedback Control Solutions To Network Level User-Equilibrium Real-Time Dynamic Traffic Assignment Problems, Pushkin Kachroo, Kaan Ozbay
Electrical & Computer Engineering Faculty Research
A new method for performing dynamic traffic assignment (DTA) is presented which is applicable in real time, since the solution is based on feedback control. This method employs the design of nonlinear H∞ feedback control systems which is robust to certain class of uncertainties in the system. The solution aims at achieving user equilibrium on alternate routes in a network setting.
Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo
Intelligent Control Of Vehicles: Preliminary Results On The Application Of Learning Automata Techniques To Automated Highway System, Cem Unsal, John S. Bay, Pushkin Kachroo
Electrical & Computer Engineering Faculty Research
We suggest an intelligent controller for an automated vehicle to plan its own trajectory based on sensor and communication data received. Our intelligent controller is based on an artificial intelligence technique called learning stochastic automata. The automaton can learn the best possible action to avoid collisions using the data received from on-board sensors. The system has the advantage of being able to work in unmodeled stochastic environments. Simulations for the lateral control of a vehicle using this AI method provides encouraging results.